Results 71 to 80 of about 10,119 (225)
Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks
International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa +5 more
wiley +1 more source
Computing resources sensitive parallelization of neural neworks for large scale diabetes data modelling, diagnosis and prediction [PDF]
, 2011 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Diabetes has become one of the most severe deceases due to an increasing number of diabetes patients globally.
Qi, Hao
core
Dache: A Data Aware Caching for Big-Data Applications Using the MapReduce Framework
Tsinghua Science and Technology, 2014 The buzz-word big-data refers to the large-scale distributed data processing applications that operate on exceptionally large amounts of data. Google’s MapReduce and Apache’s Hadoop, its open-source implementation, are the defacto software systems for ...
Yaxiong Zhao, Jie Wu, Cong Liu
doaj +1 more source
Procedia Computer Science, 2015 AbstractDespite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era.
Craig M. Vineyard +4 more
openaire +1 more source
On the Computational Complexity of MapReduce [PDF]
, 2015 In this paper we study MapReduce computations from a complexity-theoretic perspective. First, we formulate a uniform version of the MRC model of Karloff et al. (2010). We then show that the class of regular languages, and moreover all of sublogarithmic space, lies in constant round MRC. This result also applies to the MPC model of Andoni et al. (2014).
Benjamin Fish +4 more
openaire +2 more sources
International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.With the deepening of industrial digital transformation, equipment fault diagnosis faces challenges including low utilization of unstructured data, weak cross‐modal semantic association, and lagging knowledge updates. Traditional methods relying on artificial rules and static knowledge bases struggle to effectively integrate multimodal information such
Yu Fang, Richard Murray
wiley +1 more source
IEEE Access, 2018 In this paper, we discuss some challenges regarding the Hadoop framework. One of the main ones is the computing performance of Hadoop MapReduce jobs in terms of CPU, memory, and hard disk I/O. The networking side of a Hadoop cluster is another challenge,
Ali Khaleel, Hamed Al-Raweshidy
doaj +1 more source
Canadian Journal of Statistics, Volume 53, Issue 4, December 2025.Abstract Modern longitudinal data from wearable devices consist of biological signals at high‐frequency time points. Distributed statistical methods have emerged as a powerful tool to overcome the computational burden of estimation and inference with large data, but methodology for distributed functional regression remains limited.
Cole Manschot, Emily C. Hector
wiley +1 more source
MapReduce: within, outside, or on the side-by-side with parallel DBMSs?
Труды Института системного программирования РАН, 2018 The approaches of use of MapReduce technology together with analytical DBMSs are discussed. The paper considers approaches where one implements MapReduce within a kernel of a parallel DBMS, where MapReduce serves as a communication infrastructure of a ...
Sergey D. Kuznetsov.
doaj
Big data: modern approaches to storage and analysis
Труды Института системного программирования РАН, 2018 Big data challenged traditional storage and analysis systems in several new ways. In this paper we try to figure out how to overcome this challenges, why it's not possible to make it efficiently and describe three modern approaches to big data handling ...
Pavel Klemenkov, Sergey Kuznetsov
doaj +1 more source